text: import pandas as pd
  from collections import defaultdict
  #path = "Predicting Cluster Transitions with Member Engagements.csv"
  path = "Transition_Feature_Importances.csv"
  df = pd.read_csv(path, header=[0])
  
  for row in df.itertuples():
      for i,v in enumerate(row):
          i_val = i - 2
          if i_val >= 0:
              if v != "-":
                  print(list(row)[0],i_val,v)
              
  
  d = defaultdict(lambda: [])
  columns = list(df)[2:]
  for row in df.itertuples():
      for column in columns:
          value = getattr(row, column)
          if value > 0:
              d[str(row.start) + "," + str(row.end)].append((column, value))
  
  for key in list(d.keys()):
      values = d[key]
      sort = sorted(values, key = lambda x: x[1], reverse=True)
      transform = list(map(lambda x: str(x[0]) + "," + str(x[1]), sort))
      row = ",".join(transform)
      complete = key + "," + row
      print(complete)
  